• Electronics Optics & Control
  • Vol. 31, Issue 7, 8 (2024)
TANG Song1 and WU Jianyuan2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: 10.3969/j.issn.1671-637x.2024.07.002 Cite this Article
    TANG Song, WU Jianyuan. A Cooperative Trajectory Planning Method Based on Improved Genetic Algorithm[J]. Electronics Optics & Control, 2024, 31(7): 8 Copy Citation Text show less

    Abstract

    To address the issues of large computation scale and low efficiency of multi-UAV cooperative planning,a Partheno-/Bi-Parent Genetic Algorithm (PBGA) solving model is proposed.This algorithm features an improved encoding method and a single-double parent combined evolutionary strategy.The population evolution is carried out by a partheno-genetic operator,while the bi-parent genetic operator helps to escape from local optima.Simulation results demonstrate the convergence of PBGA.In small-scale and large-scale optimization scenarios,PBGA reduces the convergence iterations by 70% and 64% respectively compared with the traditional genetic algorithm.This approach holds significant reference value for addressing multi-UAV cooperative problems.